Multidisciplinary Data Scientist. More than 5 years working with Machine Learning, Research, and Project Management for international businesses. Specialized in lookalike and recommendation models, building products for marketers, insights and strategy teams.
Fluent and Working in English, Spanish, and Portuguese
Developed projects and solutions for Disney, Ford, Amazon, Best Buy, U.S. Bank, Lowe's, Victoria's Secret, Red Bull, Celsius, Haleon, NHL, Adsmovil and many more — plus venture capitals such as Positive Ventures, ALIVE, and DILA Capital.
International Relations bachelor, self-taught coding and statistics, later got a post graduation degree in Computer Science and currently pursuing my Masters. I have worked in Data Science for international businesses, focusing on machine learning, segmentation models and more recently in Artificial Intelligence with GenAI workflows. My main role is helping brands understand consumer behavior and drive favorability and purchase intent.
Developed an AutoML Pipeline to automate model tuning, cross-validation, and evaluation with a custom composite score and penalty system. Allowing classification model training and a similarity search classifier algorithm written from scratch for research data.
Designed and shipped agentic workflows: research summarization for a large-scale insights dashboard, complex RAG on internal content with time-sensitive retrieval for reliability and clear actions, and text-to-SQL so non-technical users can query data in natural language.
Developed multiple internal packages (wrappers, ETLs) for applying Machine Learning and AI into production ready solutions. Delivery in FastAPI deployments in AWS Lambda, EC2 instances and Airflow to enable Backend teams to integrate it solutions into the product.
